Multi-item EOQ model for fresh fruits with preservation technology investment,time-varying holding cost,variable deterioration and shortages

In a fruit wholesale shop,a fruiterer needs to maintain huge inventory of different ranges of fruit items for customers because of uncertainty in consumer preferences and behaviour.But demand of them may differ and different EOQ models for each item are required for optimal level of EOQ.This paper presents a single inventory model to assimilate these varieties.It is assumed that many fruit items bear constant rate of deterioration,some are with time proportional deterioration and some do not deteriorate.To control deterioration of the units in inventory,the advanced preservation technology is considered.The proposed single inventory model of this paper incorporates composite and heterogeneous features of multiple items and presents analysis for obtaining optimal level for output model parameters.

Partial backlogging inventory model with price and stock level dependent demand,time varying holding cost and quantity discounts

This article deals with an increasing total profit for inventory optimal ordered quantity and partial backlogging with the holding cost depending on the storage time period,and the rate of market demand is assumed to fluctuate as a function,based on level of stock and selling price.Thereafter,using the concept of a Hessian matrix,we have proved the concave nature of the profit function for the case where maximum cost is obtained.Finally,in order to validate the derived models,numerical examples and sensitivity analysis are explained.Through numerical test,we show that the proposed algorithms give quite satisfactory solutions.Hence,it can be concluded that the total profit can be increased by allowing shortage and partial backlogging.

Genetic Algorithm for Scheduling Problem of Chemical Batch Process with Due Date Constraints

The intense competition in the current marketplace ha s forced firms to reexamine their methods of doing business, using superior manu facturing practices in the form of just-in-time (JIT), production with JIT pra ctices pursue completion on time and zero inventory, which is often instruct ed according to the custom’s demand or the sale contract. Earliness and tardine ss are undesirable because both of them will bring the extra cost, cost will als o be increased by some factors such as operation condition, intermediate storage , clean method, etc, to minimize the total cost is often the main scheduling objective, but sometime it is most important for factories to eliminate the tar diness cost in order to maintain the commercial credit and to avoid penalty, the refore, minimum of tardiness cost becomes the first objective. It is more import ant to select a reasonable objective by the actual condition during scheduli ng. In this paper scheduling problem of chemical batch process with due date is studied, two different intermediate storage policies and two different productio n modes are also discussed, production scheduling with different intermediate st orage policy and different production mode is proposed and the result is compare d. In order to complete all products within the due date, not only earliness and tardiness but also holding problem is considered, the objective is to selec t a proper intermediate storage policy and production mode and to minimize the c ost resulted by the earliness and tardiness, even the cost result by the interme diate storage. Scheduling with multiple stage and multiple machine is known as a NP-hard problem, mathematical program (MP) method, such as branch-and-bound (BAB), mixed integer linear program (MILP), etc, is often used to solve the sche duling problem. But as is well known, MP method is not good for combination opti mization, especially for large scale and complex optimal problem, whereas geneti c algorithm (GA) can overcome the MP method’s shortcoming and is fit for solvin g such scheduling problem. In this paper a modified genetic algorithm with speci al crossover operator and mutation operator is presented to solve this schedulin g problem. The results show such problem can be solved effectively with the pres ented method.

An EPQ model with variable production,probabilistic deterioration and partial backlogging under inflation

This paper develops an economic production quantity(EPQ)model under the effect of inflation and time value of money.The rate of replenishment is considered to be a variable and the generalized unit production cost function is formulated by incorporating several factors,such as raw material,labour,replenishment rate,advertisements and other factors of the manufacturing system.The selling price of a unit is determined by a mark-up over the production cost.We have considered three types of continuous probabilistic deterioration function,and also considered that the holding cost of the item per unit time is assumed to be an increasing linear function of time spent in storage.In addition,shortages are allowed and partially backlogged.This model aids in minimizing the total inventory cost by finding the optimal cycle length and the optimal production quantity.The optimal solution of the model is illustrated with the help of numerical examples.

Analysis and optimization of an EOQ inventory model with promotional efforts and back ordering under delay in payments

In this paper,economic order quantity(EOQ)inventory model is considered subject to promotional efforts.We adopt a demand function which is dependent on sales teams’initiatives in which shortages are allowed which are completely backlogged under the condition of permissible delay in payments with timedependent holding cost.The main objective of this paper is to determine the optimal replenishment schedule and optimal order quantity to maximize the total profit.Expressions for various optimal indices are provided.First,we prove that a unique optimal replenishment schedule exists.Second,we present an effective iterative algorithm to obtain the optimal solution.Furthermore,we establish some useful theorems to characterize the optimal solution to determine the values of replenishment schedule and optimal order quantity.Third,we prove that the total profit is a concave function via differential calculus and present numerical examples using SCILAB 5.5.0 to illustrate the model.Finally,we extend the numerical example by performing a sensitivity analysis of the model parameters and discuss managerial insights.This study suggests to the management of firms to determine the optimal order quantity,optimal inventory cycle length and sales teams’initiatives/promotional effort in order to achieve their maximum profits.